Overview

Dataset statistics

Number of variables	34
Number of observations	1000
Missing cells	197
Missing cells (%)	0.6%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	2.0 MiB
Average record size in memory	2.1 KiB

Variable types

Categorical	7
Text	16
Numeric	5
Unsupported	1
DateTime	2
URL	3

Alerts

`gender` is highly overall correlated with `location.coordinates.longitude` and 1 other fields	High correlation
`id.name` is highly overall correlated with `location.coordinates.longitude` and 2 other fields	High correlation
`location.coordinates.longitude` is highly overall correlated with `gender` and 6 other fields	High correlation
`location.country` is highly overall correlated with `id.name` and 2 other fields	High correlation
`location.timezone.description` is highly overall correlated with `location.coordinates.longitude` and 1 other fields	High correlation
`location.timezone.offset` is highly overall correlated with `location.coordinates.longitude` and 1 other fields	High correlation
`name.title` is highly overall correlated with `gender` and 1 other fields	High correlation
`nat` is highly overall correlated with `id.name` and 2 other fields	High correlation
`id.value` has 197 (19.7%) missing values	Missing
`phone` has unique values	Unique
`cell` has unique values	Unique
`location.coordinates.longitude` has unique values	Unique
`login.uuid` has unique values	Unique
`login.salt` has unique values	Unique
`login.md5` has unique values	Unique
`login.sha1` has unique values	Unique
`login.sha256` has unique values	Unique
`dob.date` has unique values	Unique
`registered.date` has unique values	Unique
`location.postcode` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2026-01-28 21:19:02.971770
Analysis finished	2026-01-28 21:21:48.459963
Duration	2 minutes and 45.49 seconds
Software version	ydata-profiling vv4.18.1
Download configuration	config.json

gender
Categorical

High correlation

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	52.8 KiB

male	524
female	476

Length

Max length	6
Median length	4
Mean length	4.952
Min length	4

Characters and Unicode

Total characters	4952
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	female
2nd row	female
3rd row	male
4th row	male
5th row	male

Common Values

Value	Count	Frequency (%)
male	524	52.4%
female	476	47.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
male	524	52.4%
female	476	47.6%

Most occurring characters

Value	Count	Frequency (%)
e	1476	29.8%
m	1000	20.2%
a	1000	20.2%
l	1000	20.2%
f	476	9.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	4952	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1476	29.8%
m	1000	20.2%
a	1000	20.2%
l	1000	20.2%
f	476	9.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	4952	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1476	29.8%
m	1000	20.2%
a	1000	20.2%
l	1000	20.2%
f	476	9.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	4952	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1476	29.8%
m	1000	20.2%
a	1000	20.2%
l	1000	20.2%
f	476	9.6%

email
Text

Distinct	997
Distinct (%)	99.7%
Missing	0
Missing (%)	0.0%
Memory size	72.6 KiB

Length

Max length	39
Median length	33
Mean length	25.212
Min length	19

Characters and Unicode

Total characters	25212
Distinct characters	30
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	994 ?
Unique (%)	99.4%

Sample

1st row	supriya.bangera@example.com
2nd row	angelika.greve@example.com
3rd row	naim.molendijk@example.com
4th row	cristobal.trevino@example.com
5th row	francesco.ulrich@example.com

Value	Count	Frequency (%)
matteo.andre@example.com	2	0.2%
cecilie.madsen@example.com	2	0.2%
awyn.njty@example.com	2	0.2%
wendy.hale@example.com	1	0.1%
laly.petit@example.com	1	0.1%
radomisl.kril@example.com	1	0.1%
dragan.borojevic@example.com	1	0.1%
ines.escalante@example.com	1	0.1%
naim.molendijk@example.com	1	0.1%
cristobal.trevino@example.com	1	0.1%
Other values (987)	987	98.7%

Most occurring characters

Value	Count	Frequency (%)
e	3289	13.0%
a	2501	9.9%
m	2443	9.7%
.	2000	7.9%
l	1782	7.1%
o	1750	6.9%
c	1367	5.4%
p	1164	4.6%
x	1025	4.1%
@	1000	4.0%
Other values (20)	6891	27.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	25212	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	3289	13.0%
a	2501	9.9%
m	2443	9.7%
.	2000	7.9%
l	1782	7.1%
o	1750	6.9%
c	1367	5.4%
p	1164	4.6%
x	1025	4.1%
@	1000	4.0%
Other values (20)	6891	27.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	25212	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	3289	13.0%
a	2501	9.9%
m	2443	9.7%
.	2000	7.9%
l	1782	7.1%
o	1750	6.9%
c	1367	5.4%
p	1164	4.6%
x	1025	4.1%
@	1000	4.0%
Other values (20)	6891	27.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	25212	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	3289	13.0%
a	2501	9.9%
m	2443	9.7%
.	2000	7.9%
l	1782	7.1%
o	1750	6.9%
c	1367	5.4%
p	1164	4.6%
x	1025	4.1%
@	1000	4.0%
Other values (20)	6891	27.3%

phone
Text

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	59.8 KiB

Length

Max length	16
Median length	14
Mean length	12.145
Min length	8

Characters and Unicode

Total characters	12145
Distinct characters	39
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	7441853155
2nd row	0299-7266921
3rd row	(073) 4576715
4th row	(614) 832 1069
5th row	0231-2739158

Value	Count	Frequency (%)
079	12	0.8%
077	12	0.8%
068	10	0.7%
075	10	0.7%
066	9	0.6%
078	8	0.5%
096	8	0.5%
098	8	0.5%
067	7	0.5%
83	5	0.3%
Other values (1296)	1412	94.1%

Most occurring characters

Value	Count	Frequency (%)
0	1331	11.0%
-	1154	9.5%
7	1018	8.4%
9	956	7.9%
6	949	7.8%
1	940	7.7%
5	939	7.7%
8	917	7.6%
2	909	7.5%
3	894	7.4%
Other values (29)	2138	17.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	12145	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	1331	11.0%
-	1154	9.5%
7	1018	8.4%
9	956	7.9%
6	949	7.8%
1	940	7.7%
5	939	7.7%
8	917	7.6%
2	909	7.5%
3	894	7.4%
Other values (29)	2138	17.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	12145	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	1331	11.0%
-	1154	9.5%
7	1018	8.4%
9	956	7.9%
6	949	7.8%
1	940	7.7%
5	939	7.7%
8	917	7.6%
2	909	7.5%
3	894	7.4%
Other values (29)	2138	17.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	12145	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	1331	11.0%
-	1154	9.5%
7	1018	8.4%
9	956	7.9%
6	949	7.8%
1	940	7.7%
5	939	7.7%
8	917	7.6%
2	909	7.5%
3	894	7.4%
Other values (29)	2138	17.6%

cell
Text

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	60.0 KiB

Length

Max length	14
Median length	13
Mean length	12.3
Min length	8

Characters and Unicode

Total characters	12300
Distinct characters	40
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	8275260265
2nd row	0176-8590933
3rd row	(06) 25012167
4th row	(672) 391 7823
5th row	0178-6362153

Value	Count	Frequency (%)
06	47	3.2%
078	11	0.7%
079	10	0.7%
075	9	0.6%
098	9	0.6%
076	8	0.5%
096	8	0.5%
099	7	0.5%
097	7	0.5%
066	6	0.4%
Other values (1268)	1368	91.8%

Most occurring characters

Value	Count	Frequency (%)
0	1312	10.7%
-	1245	10.1%
6	1104	9.0%
7	1062	8.6%
1	963	7.8%
8	953	7.7%
9	931	7.6%
4	909	7.4%
5	873	7.1%
2	853	6.9%
Other values (30)	2095	17.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	12300	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	1312	10.7%
-	1245	10.1%
6	1104	9.0%
7	1062	8.6%
1	963	7.8%
8	953	7.7%
9	931	7.6%
4	909	7.4%
5	873	7.1%
2	853	6.9%
Other values (30)	2095	17.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	12300	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	1312	10.7%
-	1245	10.1%
6	1104	9.0%
7	1062	8.6%
1	963	7.8%
8	953	7.7%
9	931	7.6%
4	909	7.4%
5	873	7.1%
2	853	6.9%
Other values (30)	2095	17.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	12300	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	1312	10.7%
-	1245	10.1%
6	1104	9.0%
7	1062	8.6%
1	963	7.8%
8	953	7.7%
9	931	7.6%
4	909	7.4%
5	873	7.1%
2	853	6.9%
Other values (30)	2095	17.0%

nat
Categorical

High correlation

Distinct	21
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Memory size	49.9 KiB

DE	60
NO	60
TR	54
GB	53
RS	52
Other values (16)	721

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	2000
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	IN
2nd row	DE
3rd row	NL
4th row	MX
5th row	DE

Common Values

Value	Count	Frequency (%)
DE	60	6.0%
NO	60	6.0%
TR	54	5.4%
GB	53	5.3%
RS	52	5.2%
FR	52	5.2%
IE	51	5.1%
IR	51	5.1%
NZ	48	4.8%
ES	47	4.7%
Other values (11)	472	47.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
de	60	6.0%
no	60	6.0%
tr	54	5.4%
gb	53	5.3%
rs	52	5.2%
fr	52	5.2%
ie	51	5.1%
ir	51	5.1%
nz	48	4.8%
es	47	4.7%
Other values (11)	472	47.2%

Most occurring characters

Value	Count	Frequency (%)
R	254	12.7%
N	200	10.0%
I	188	9.4%
E	158	7.9%
S	143	7.1%
U	128	6.4%
A	122	6.1%
D	101	5.1%
B	98	4.9%
F	92	4.6%
Other values (10)	516	25.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
R	254	12.7%
N	200	10.0%
I	188	9.4%
E	158	7.9%
S	143	7.1%
U	128	6.4%
A	122	6.1%
D	101	5.1%
B	98	4.9%
F	92	4.6%
Other values (10)	516	25.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
R	254	12.7%
N	200	10.0%
I	188	9.4%
E	158	7.9%
S	143	7.1%
U	128	6.4%
A	122	6.1%
D	101	5.1%
B	98	4.9%
F	92	4.6%
Other values (10)	516	25.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
R	254	12.7%
N	200	10.0%
I	188	9.4%
E	158	7.9%
S	143	7.1%
U	128	6.4%
A	122	6.1%
D	101	5.1%
B	98	4.9%
F	92	4.6%
Other values (10)	516	25.8%

name.title
Categorical

High correlation

Distinct	7
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	50.6 KiB

Mr	493
Ms	164
Miss	157
Mrs	142
Monsieur	31
Other values (2)	13

Length

Max length	12
Median length	2
Mean length	2.712
Min length	2

Characters and Unicode

Total characters	2712
Distinct characters	12
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Ms
2nd row	Mrs
3rd row	Mr
4th row	Mr
5th row	Mr

Common Values

Value	Count	Frequency (%)
Mr	493	49.3%
Ms	164	16.4%
Miss	157	15.7%
Mrs	142	14.2%
Monsieur	31	3.1%
Madame	10	1.0%
Mademoiselle	3	0.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
mr	493	49.3%
ms	164	16.4%
miss	157	15.7%
mrs	142	14.2%
monsieur	31	3.1%
madame	10	1.0%
mademoiselle	3	0.3%

Most occurring characters

Value	Count	Frequency (%)
M	1000	36.9%
r	666	24.6%
s	654	24.1%
i	191	7.0%
e	50	1.8%
o	34	1.3%
n	31	1.1%
u	31	1.1%
a	23	0.8%
d	13	0.5%
Other values (2)	19	0.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2712	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
M	1000	36.9%
r	666	24.6%
s	654	24.1%
i	191	7.0%
e	50	1.8%
o	34	1.3%
n	31	1.1%
u	31	1.1%
a	23	0.8%
d	13	0.5%
Other values (2)	19	0.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2712	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
M	1000	36.9%
r	666	24.6%
s	654	24.1%
i	191	7.0%
e	50	1.8%
o	34	1.3%
n	31	1.1%
u	31	1.1%
a	23	0.8%
d	13	0.5%
Other values (2)	19	0.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2712	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
M	1000	36.9%
r	666	24.6%
s	654	24.1%
i	191	7.0%
e	50	1.8%
o	34	1.3%
n	31	1.1%
u	31	1.1%
a	23	0.8%
d	13	0.5%
Other values (2)	19	0.7%

name.first
Text

Distinct	828
Distinct (%)	82.8%
Missing	0
Missing (%)	0.0%
Memory size	56.5 KiB

Length

Max length	14
Median length	13
Mean length	5.779
Min length	2

Characters and Unicode

Total characters	5779
Distinct characters	98
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	693 ?
Unique (%)	69.3%

Sample

1st row	Supriya
2nd row	Angelika
3rd row	Naïm
4th row	Cristobal
5th row	Francesco

Value	Count	Frequency (%)
terry	4	0.4%
josé	4	0.4%
justine	4	0.4%
julia	4	0.4%
matteo	4	0.4%
hugo	4	0.4%
olivia	4	0.4%
ava	4	0.4%
cecilie	3	0.3%
batur	3	0.3%
Other values (818)	965	96.2%

Most occurring characters

Value	Count	Frequency (%)
a	722	12.5%
i	508	8.8%
e	496	8.6%
n	389	6.7%
r	349	6.0%
l	344	6.0%
o	295	5.1%
s	185	3.2%
t	166	2.9%
m	137	2.4%
Other values (88)	2188	37.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5779	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	722	12.5%
i	508	8.8%
e	496	8.6%
n	389	6.7%
r	349	6.0%
l	344	6.0%
o	295	5.1%
s	185	3.2%
t	166	2.9%
m	137	2.4%
Other values (88)	2188	37.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5779	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	722	12.5%
i	508	8.8%
e	496	8.6%
n	389	6.7%
r	349	6.0%
l	344	6.0%
o	295	5.1%
s	185	3.2%
t	166	2.9%
m	137	2.4%
Other values (88)	2188	37.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5779	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	722	12.5%
i	508	8.8%
e	496	8.6%
n	389	6.7%
r	349	6.0%
l	344	6.0%
o	295	5.1%
s	185	3.2%
t	166	2.9%
m	137	2.4%
Other values (88)	2188	37.9%

name.last
Text

Distinct	754
Distinct (%)	75.4%
Missing	0
Missing (%)	0.0%
Memory size	60.6 KiB

Length

Max length	20
Median length	14
Mean length	6.536
Min length	2

Characters and Unicode

Total characters	6536
Distinct characters	108
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	585 ?
Unique (%)	58.5%

Sample

1st row	Bangera
2nd row	Greve
3rd row	Molendijk
4th row	Treviño
5th row	Ulrich

Value	Count	Frequency (%)
da	9	0.9%
كامياران	7	0.7%
van	6	0.6%
lucas	5	0.5%
almeida	5	0.5%
white	5	0.5%
احمدی	4	0.4%
نجاتی	4	0.4%
fernandez	4	0.4%
flores	4	0.4%
Other values (755)	975	94.8%

Most occurring characters

Value	Count	Frequency (%)
e	675	10.3%
a	592	9.1%
n	474	7.3%
r	472	7.2%
i	383	5.9%
o	376	5.8%
l	306	4.7%
s	297	4.5%
t	216	3.3%
u	158	2.4%
Other values (98)	2587	39.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6536	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	675	10.3%
a	592	9.1%
n	474	7.3%
r	472	7.2%
i	383	5.9%
o	376	5.8%
l	306	4.7%
s	297	4.5%
t	216	3.3%
u	158	2.4%
Other values (98)	2587	39.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6536	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	675	10.3%
a	592	9.1%
n	474	7.3%
r	472	7.2%
i	383	5.9%
o	376	5.8%
l	306	4.7%
s	297	4.5%
t	216	3.3%
u	158	2.4%
Other values (98)	2587	39.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6536	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	675	10.3%
a	592	9.1%
n	474	7.3%
r	472	7.2%
i	383	5.9%
o	376	5.8%
l	306	4.7%
s	297	4.5%
t	216	3.3%
u	158	2.4%
Other values (98)	2587	39.6%

location.street.number
Real number (ℝ)

Distinct	956
Distinct (%)	95.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5014.422

Minimum	1
Maximum	9996
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	1
5-th percentile	485.75
Q1	2496.5
median	4959
Q3	7455
95-th percentile	9580.1
Maximum	9996
Range	9995
Interquartile range (IQR)	4958.5

Descriptive statistics

Standard deviation	2902.3513
Coefficient of variation (CV)	0.57880077
Kurtosis	-1.1661259
Mean	5014.422
Median Absolute Deviation (MAD)	2477.5
Skewness	0.018972678
Sum	5014422
Variance	8423643.2
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
5346	2	0.2%
6312	2	0.2%
8859	2	0.2%
114	2	0.2%
486	2	0.2%
9456	2	0.2%
3886	2	0.2%
1229	2	0.2%
1421	2	0.2%
2208	2	0.2%
Other values (946)	980	98.0%

Value	Count	Frequency (%)
1	1	0.1%
17	1	0.1%
35	2	0.2%
46	1	0.1%
49	1	0.1%
50	1	0.1%
69	1	0.1%
84	1	0.1%
92	1	0.1%
96	1	0.1%

Value	Count	Frequency (%)
9996	1	0.1%
9976	1	0.1%
9967	1	0.1%
9966	1	0.1%
9955	1	0.1%
9946	1	0.1%
9943	1	0.1%
9917	1	0.1%
9895	1	0.1%
9884	1	0.1%

location.street.name
Text

Distinct	746
Distinct (%)	74.6%
Missing	0
Missing (%)	0.0%
Memory size	69.7 KiB

Length

Max length	46
Median length	24
Mean length	13.131
Min length	3

Characters and Unicode

Total characters	13131
Distinct characters	130
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	579 ?
Unique (%)	57.9%

Sample

1st row	Hazratganj
2nd row	Parkstraße
3rd row	Burgemeester Dohmenplein
4th row	Privada Sur Madrigal
5th row	Goethestraße

Value	Count	Frequency (%)
de	81	4.0%
rue	72	3.5%
road	55	2.7%
rd	53	2.6%
street	53	2.6%
cd	49	2.4%
st	46	2.3%
rua	42	2.1%
calle	36	1.8%
la	24	1.2%
Other values (930)	1528	74.9%

Most occurring characters

Value	Count	Frequency (%)
e	1387	10.6%
a	1304	9.9%
	1078	8.2%
r	768	5.8%
i	642	4.9%
n	614	4.7%
t	611	4.7%
l	569	4.3%
o	547	4.2%
d	496	3.8%
Other values (120)	5115	39.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13131	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	1387	10.6%
a	1304	9.9%
	1078	8.2%
r	768	5.8%
i	642	4.9%
n	614	4.7%
t	611	4.7%
l	569	4.3%
o	547	4.2%
d	496	3.8%
Other values (120)	5115	39.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13131	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	1387	10.6%
a	1304	9.9%
	1078	8.2%
r	768	5.8%
i	642	4.9%
n	614	4.7%
t	611	4.7%
l	569	4.3%
o	547	4.2%
d	496	3.8%
Other values (120)	5115	39.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13131	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	1387	10.6%
a	1304	9.9%
	1078	8.2%
r	768	5.8%
i	642	4.9%
n	614	4.7%
t	611	4.7%
l	569	4.3%
o	547	4.2%
d	496	3.8%
Other values (120)	5115	39.0%

location.city
Text

Distinct	825
Distinct (%)	82.5%
Missing	0
Missing (%)	0.0%
Memory size	62.5 KiB

Length

Max length	28
Median length	24
Mean length	8.68
Min length	2

Characters and Unicode

Total characters	8680
Distinct characters	120
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	694 ?
Unique (%)	69.4%

Sample

1st row	Karimnagar
2nd row	Kuppenheim
3rd row	Mook
4th row	General Zaragoza
5th row	Gräfenhainichen

Value	Count	Frequency (%)
de	24	2.0%
la	13	1.1%
san	7	0.6%
nelson	5	0.4%
hastings	5	0.4%
am	5	0.4%
santa	4	0.3%
bad	4	0.3%
plymouth	4	0.3%
st	4	0.3%
Other values (932)	1141	93.8%

Most occurring characters

Value	Count	Frequency (%)
a	834	9.6%
e	735	8.5%
n	625	7.2%
r	601	6.9%
i	496	5.7%
o	493	5.7%
l	421	4.9%
t	325	3.7%
s	318	3.7%
u	317	3.7%
Other values (110)	3515	40.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8680	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	834	9.6%
e	735	8.5%
n	625	7.2%
r	601	6.9%
i	496	5.7%
o	493	5.7%
l	421	4.9%
t	325	3.7%
s	318	3.7%
u	317	3.7%
Other values (110)	3515	40.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8680	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	834	9.6%
e	735	8.5%
n	625	7.2%
r	601	6.9%
i	496	5.7%
o	493	5.7%
l	421	4.9%
t	325	3.7%
s	318	3.7%
u	317	3.7%
Other values (110)	3515	40.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8680	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	834	9.6%
e	735	8.5%
n	625	7.2%
r	601	6.9%
i	496	5.7%
o	493	5.7%
l	421	4.9%
t	325	3.7%
s	318	3.7%
u	317	3.7%
Other values (110)	3515	40.5%

location.state
Text

Distinct	461
Distinct (%)	46.1%
Missing	0
Missing (%)	0.0%
Memory size	63.5 KiB

Length

Max length	28
Median length	21
Mean length	9.803
Min length	2

Characters and Unicode

Total characters	9803
Distinct characters	107
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	194 ?
Unique (%)	19.4%

Sample

1st row	Himachal Pradesh
2nd row	Berlin
3rd row	Groningen
4th row	Queretaro
5th row	Hessen

Value	Count	Frequency (%)
south	16	1.3%
australia	12	0.9%
north	11	0.9%
west	11	0.9%
and	10	0.8%
tasmania	10	0.8%
territory	10	0.8%
sjælland	9	0.7%
hovedstaden	8	0.6%
county	8	0.6%
Other values (497)	1173	91.8%

Most occurring characters

Value	Count	Frequency (%)
a	1174	12.0%
r	694	7.1%
e	688	7.0%
n	687	7.0%
o	530	5.4%
i	529	5.4%
s	435	4.4%
l	420	4.3%
t	401	4.1%
d	339	3.5%
Other values (97)	3906	39.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	9803	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	1174	12.0%
r	694	7.1%
e	688	7.0%
n	687	7.0%
o	530	5.4%
i	529	5.4%
s	435	4.4%
l	420	4.3%
t	401	4.1%
d	339	3.5%
Other values (97)	3906	39.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	9803	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	1174	12.0%
r	694	7.1%
e	688	7.0%
n	687	7.0%
o	530	5.4%
i	529	5.4%
s	435	4.4%
l	420	4.3%
t	401	4.1%
d	339	3.5%
Other values (97)	3906	39.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	9803	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	1174	12.0%
r	694	7.1%
e	688	7.0%
n	687	7.0%
o	530	5.4%
i	529	5.4%
s	435	4.4%
l	420	4.3%
t	401	4.1%
d	339	3.5%
Other values (97)	3906	39.8%

location.country
Categorical

High correlation

Distinct	21
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Memory size	55.4 KiB

Germany	60
Norway	60
Turkey	54
United Kingdom	53
Serbia	52
Other values (16)	721

Length

Max length	14
Median length	13
Mean length	7.583
Min length	4

Characters and Unicode

Total characters	7583
Distinct characters	37
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	India
2nd row	Germany
3rd row	Netherlands
4th row	Mexico
5th row	Germany

Common Values

Value	Count	Frequency (%)
Germany	60	6.0%
Norway	60	6.0%
Turkey	54	5.4%
United Kingdom	53	5.3%
Serbia	52	5.2%
France	52	5.2%
Ireland	51	5.1%
Iran	51	5.1%
New Zealand	48	4.8%
Spain	47	4.7%
Other values (11)	472	47.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
united	97	8.5%
germany	60	5.2%
norway	60	5.2%
turkey	54	4.7%
kingdom	53	4.6%
serbia	52	4.5%
france	52	4.5%
ireland	51	4.5%
iran	51	4.5%
new	48	4.2%
Other values (13)	567	49.5%

Most occurring characters

Value	Count	Frequency (%)
a	1013	13.4%
n	798	10.5%
e	771	10.2%
r	640	8.4%
i	552	7.3%
d	463	6.1%
t	315	4.2%
l	314	4.1%
S	187	2.5%
y	174	2.3%
Other values (27)	2356	31.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	7583	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	1013	13.4%
n	798	10.5%
e	771	10.2%
r	640	8.4%
i	552	7.3%
d	463	6.1%
t	315	4.2%
l	314	4.1%
S	187	2.5%
y	174	2.3%
Other values (27)	2356	31.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	7583	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	1013	13.4%
n	798	10.5%
e	771	10.2%
r	640	8.4%
i	552	7.3%
d	463	6.1%
t	315	4.2%
l	314	4.1%
S	187	2.5%
y	174	2.3%
Other values (27)	2356	31.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	7583	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	1013	13.4%
n	798	10.5%
e	771	10.2%
r	640	8.4%
i	552	7.3%
d	463	6.1%
t	315	4.2%
l	314	4.1%
S	187	2.5%
y	174	2.3%
Other values (27)	2356	31.1%

location.postcode
Unsupported

Rejected Unsupported

Missing	0
Missing (%)	0.0%
Memory size	39.0 KiB

location.coordinates.latitude
Real number (ℝ)

Distinct	999
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.2986731

Minimum	-89.9766
Maximum	89.8873
Zeros	0
Zeros (%)	0.0%
Negative	495
Negative (%)	49.5%
Memory size	7.9 KiB

Quantile statistics

Minimum	-89.9766
5-th percentile	-81.10151
Q1	-47.04245
median	1.381
Q3	46.385275
95-th percentile	80.856145
Maximum	89.8873
Range	179.8639
Interquartile range (IQR)	93.427725

Descriptive statistics

Standard deviation	52.669249
Coefficient of variation (CV)	-176.34413
Kurtosis	-1.2452072
Mean	-0.2986731
Median Absolute Deviation (MAD)	47.0171
Skewness	0.0013359595
Sum	-298.6731
Variance	2774.0497
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
21.5262	2	0.2%
11.9114	1	0.1%
-4.1994	1	0.1%
-84.8678	1	0.1%
4.2858	1	0.1%
36.2737	1	0.1%
7.1826	1	0.1%
-75.7655	1	0.1%
-18.6211	1	0.1%
88.9682	1	0.1%
Other values (989)	989	98.9%

Value	Count	Frequency (%)
-89.9766	1	0.1%
-89.6937	1	0.1%
-89.6177	1	0.1%
-89.5512	1	0.1%
-89.2907	1	0.1%
-89.2666	1	0.1%
-88.709	1	0.1%
-88.5846	1	0.1%
-88.072	1	0.1%
-87.2354	1	0.1%

Value	Count	Frequency (%)
89.8873	1	0.1%
89.7993	1	0.1%
89.7415	1	0.1%
89.6327	1	0.1%
88.9682	1	0.1%
88.9235	1	0.1%
88.805	1	0.1%
88.7339	1	0.1%
88.6461	1	0.1%
88.6235	1	0.1%

location.coordinates.longitude
Real number (ℝ)

High correlation Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.001573

Minimum	-179.9206
Maximum	179.3478
Zeros	0
Zeros (%)	0.0%
Negative	473
Negative (%)	47.3%
Memory size	7.9 KiB

Quantile statistics

Minimum	-179.9206
5-th percentile	-163.39261
Q1	-80.831475
median	9.24785
Q3	90.948
95-th percentile	162.5145
Maximum	179.3478
Range	359.2684
Interquartile range (IQR)	171.77948

Descriptive statistics

Standard deviation	103.34161
Coefficient of variation (CV)	20.661823
Kurtosis	-1.1576603
Mean	5.001573
Median Absolute Deviation (MAD)	85.9996
Skewness	-0.099609371
Sum	5001.573
Variance	10679.489
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
112.3948	1	0.1%
-161.647	1	0.1%
-164.3181	1	0.1%
-22.5929	1	0.1%
-115.4612	1	0.1%
-72.5417	1	0.1%
-165.9229	1	0.1%
28.8191	1	0.1%
-69.251	1	0.1%
-27.6638	1	0.1%
Other values (990)	990	99.0%

Value	Count	Frequency (%)
-179.9206	1	0.1%
-179.7854	1	0.1%
-179.7505	1	0.1%
-179.7465	1	0.1%
-179.739	1	0.1%
-179.5848	1	0.1%
-179.4755	1	0.1%
-178.8448	1	0.1%
-178.2364	1	0.1%
-177.1402	1	0.1%

Value	Count	Frequency (%)
179.3478	1	0.1%
178.865	1	0.1%
178.09	1	0.1%
177.3681	1	0.1%
176.6643	1	0.1%
176.6287	1	0.1%
176.5867	1	0.1%
176.4715	1	0.1%
176.3031	1	0.1%
176.2876	1	0.1%

location.timezone.offset
Categorical

High correlation

Distinct	30
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	53.0 KiB

-6:00	47
-2:00	46
+2:00	43
+1:00	42
-9:00	39
Other values (25)	783

Length

Max length	6
Median length	5
Mean length	5.135
Min length	4

Characters and Unicode

Total characters	5135
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	-5:00
2nd row	-6:00
3rd row	+9:00
4th row	-4:00
5th row	+5:30

Common Values

Value	Count	Frequency (%)
-6:00	47	4.7%
-2:00	46	4.6%
+2:00	43	4.3%
+1:00	42	4.2%
-9:00	39	3.9%
-5:00	38	3.8%
+3:30	37	3.7%
-3:00	37	3.7%
+6:00	37	3.7%
+8:00	36	3.6%
Other values (20)	598	59.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2:00	89	8.9%
6:00	84	8.4%
9:00	73	7.3%
3:30	69	6.9%
5:00	68	6.8%
3:00	67	6.7%
4:00	67	6.7%
10:00	65	6.5%
7:00	63	6.3%
11:00	63	6.3%
Other values (8)	292	29.2%

Most occurring characters

Value	Count	Frequency (%)
0	1877	36.6%
:	1000	19.5%
+	530	10.3%
-	442	8.6%
3	296	5.8%
1	285	5.6%
5	149	2.9%
4	127	2.5%
2	124	2.4%
9	107	2.1%
Other values (3)	198	3.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	5135	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	1877	36.6%
:	1000	19.5%
+	530	10.3%
-	442	8.6%
3	296	5.8%
1	285	5.6%
5	149	2.9%
4	127	2.5%
2	124	2.4%
9	107	2.1%
Other values (3)	198	3.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	5135	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	1877	36.6%
:	1000	19.5%
+	530	10.3%
-	442	8.6%
3	296	5.8%
1	285	5.6%
5	149	2.9%
4	127	2.5%
2	124	2.4%
9	107	2.1%
Other values (3)	198	3.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	5135	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	1877	36.6%
:	1000	19.5%
+	530	10.3%
-	442	8.6%
3	296	5.8%
1	285	5.6%
5	149	2.9%
4	127	2.5%
2	124	2.4%
9	107	2.1%
Other values (3)	198	3.9%

location.timezone.description
Categorical

High correlation

Distinct	30
Distinct (%)	3.0%
Missing	0
Missing (%)	0.0%
Memory size	73.4 KiB

Central Time (US & Canada), Mexico City	47
Mid-Atlantic	46
Kaliningrad, South Africa	43
Brussels, Copenhagen, Madrid, Paris	42
Alaska	39
Other values (25)	783

Length

Max length	47
Median length	36
Mean length	26.074
Min length	5

Characters and Unicode

Total characters	26074
Distinct characters	54
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Eastern Time (US & Canada), Bogota, Lima
2nd row	Central Time (US & Canada), Mexico City
3rd row	Tokyo, Seoul, Osaka, Sapporo, Yakutsk
4th row	Atlantic Time (Canada), Caracas, La Paz
5th row	Bombay, Calcutta, Madras, New Delhi

Common Values

Value	Count	Frequency (%)
Central Time (US & Canada), Mexico City	47	4.7%
Mid-Atlantic	46	4.6%
Kaliningrad, South Africa	43	4.3%
Brussels, Copenhagen, Madrid, Paris	42	4.2%
Alaska	39	3.9%
Eastern Time (US & Canada), Bogota, Lima	38	3.8%
Tehran	37	3.7%
Brazil, Buenos Aires, Georgetown	37	3.7%
Almaty, Dhaka, Colombo	37	3.7%
Beijing, Perth, Singapore, Hong Kong	36	3.6%
Other values (20)	598	59.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
time	198	5.5%
canada	170	4.7%
us	135	3.8%
	135	3.8%
eastern	70	1.9%
new	55	1.5%
central	47	1.3%
mexico	47	1.3%
city	47	1.3%
islands	47	1.3%
Other values (81)	2647	73.6%

Most occurring characters

Value	Count	Frequency (%)
a	3270	12.5%
	2598	10.0%
i	1547	5.9%
,	1488	5.7%
n	1485	5.7%
e	1367	5.2%
o	1297	5.0%
r	977	3.7%
t	971	3.7%
s	955	3.7%
Other values (44)	10119	38.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	26074	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	3270	12.5%
	2598	10.0%
i	1547	5.9%
,	1488	5.7%
n	1485	5.7%
e	1367	5.2%
o	1297	5.0%
r	977	3.7%
t	971	3.7%
s	955	3.7%
Other values (44)	10119	38.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	26074	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	3270	12.5%
	2598	10.0%
i	1547	5.9%
,	1488	5.7%
n	1485	5.7%
e	1367	5.2%
o	1297	5.0%
r	977	3.7%
t	971	3.7%
s	955	3.7%
Other values (44)	10119	38.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	26074	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	3270	12.5%
	2598	10.0%
i	1547	5.9%
,	1488	5.7%
n	1485	5.7%
e	1367	5.2%
o	1297	5.0%
r	977	3.7%
t	971	3.7%
s	955	3.7%
Other values (44)	10119	38.8%

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	83.1 KiB

Length

Max length	36
Median length	36
Mean length	36
Min length	36

Characters and Unicode

Total characters	36000
Distinct characters	17
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	e1c48576-63a7-4373-8016-d0cf95662e96
2nd row	864c9490-4a8b-4943-8d7a-719d3b0493cb
3rd row	938f117a-1589-4367-83ef-b399f42bd8f0
4th row	69e2b7a7-d638-4539-a4c8-c4492ec64ab5
5th row	bab2865c-7349-48f6-b812-429b28037a1a

Value	Count	Frequency (%)
e1c48576-63a7-4373-8016-d0cf95662e96	1	0.1%
8b6318f5-ecce-4312-9a70-ebd42284d140	1	0.1%
a5b69844-76ab-49d4-9ffb-e8892346afb0	1	0.1%
99e6114f-3505-42e0-b487-48bbeba02a07	1	0.1%
938f117a-1589-4367-83ef-b399f42bd8f0	1	0.1%
69e2b7a7-d638-4539-a4c8-c4492ec64ab5	1	0.1%
bab2865c-7349-48f6-b812-429b28037a1a	1	0.1%
6478a13e-4ad5-4ad9-a5f9-d5072aadd417	1	0.1%
421afc35-e2bd-444d-863d-21816b374eb7	1	0.1%
6bdef1e6-7882-427e-bb46-24b6e18dda4a	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
-	4000	11.1%
4	2905	8.1%
b	2187	6.1%
a	2079	5.8%
8	2062	5.7%
9	2051	5.7%
6	1983	5.5%
d	1937	5.4%
1	1929	5.4%
3	1900	5.3%
Other values (7)	12967	36.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	36000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
-	4000	11.1%
4	2905	8.1%
b	2187	6.1%
a	2079	5.8%
8	2062	5.7%
9	2051	5.7%
6	1983	5.5%
d	1937	5.4%
1	1929	5.4%
3	1900	5.3%
Other values (7)	12967	36.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	36000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
-	4000	11.1%
4	2905	8.1%
b	2187	6.1%
a	2079	5.8%
8	2062	5.7%
9	2051	5.7%
6	1983	5.5%
d	1937	5.4%
1	1929	5.4%
3	1900	5.3%
Other values (7)	12967	36.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	36000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
-	4000	11.1%
4	2905	8.1%
b	2187	6.1%
a	2079	5.8%
8	2062	5.7%
9	2051	5.7%
6	1983	5.5%
d	1937	5.4%
1	1929	5.4%
3	1900	5.3%
Other values (7)	12967	36.0%

Distinct	999
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	61.1 KiB

Length

Max length	21
Median length	19
Mean length	13.417
Min length	9

Characters and Unicode

Total characters	13417
Distinct characters	33
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	998 ?
Unique (%)	99.8%

Sample

1st row	happyswan109
2nd row	lazymeercat294
3rd row	bluewolf781
4th row	blackostrich700
5th row	blackcat544

Value	Count	Frequency (%)
smallleopard599	2	0.2%
bigkoala675	1	0.1%
orangemeercat398	1	0.1%
yellowbird850	1	0.1%
bluewolf781	1	0.1%
blackostrich700	1	0.1%
blackcat544	1	0.1%
purpleleopard193	1	0.1%
redzebra223	1	0.1%
orangecat258	1	0.1%
Other values (989)	989	98.9%

Most occurring characters

Value	Count	Frequency (%)
a	1121	8.4%
e	988	7.4%
l	871	6.5%
r	795	5.9%
o	659	4.9%
i	600	4.5%
g	494	3.7%
t	487	3.6%
n	475	3.5%
b	459	3.4%
Other values (23)	6468	48.2%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	13417	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	1121	8.4%
e	988	7.4%
l	871	6.5%
r	795	5.9%
o	659	4.9%
i	600	4.5%
g	494	3.7%
t	487	3.6%
n	475	3.5%
b	459	3.4%
Other values (23)	6468	48.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	13417	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	1121	8.4%
e	988	7.4%
l	871	6.5%
r	795	5.9%
o	659	4.9%
i	600	4.5%
g	494	3.7%
t	487	3.6%
n	475	3.5%
b	459	3.4%
Other values (23)	6468	48.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	13417	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	1121	8.4%
e	988	7.4%
l	871	6.5%
r	795	5.9%
o	659	4.9%
i	600	4.5%
g	494	3.7%
t	487	3.6%
n	475	3.5%
b	459	3.4%
Other values (23)	6468	48.2%

Distinct	935
Distinct (%)	93.5%
Missing	0
Missing (%)	0.0%
Memory size	54.1 KiB

Length

Max length	11
Median length	9
Mean length	6.236
Min length	4

Characters and Unicode

Total characters	6236
Distinct characters	38
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	872 ?
Unique (%)	87.2%

Sample

1st row	asian
2nd row	freee
3rd row	maryland
4th row	hunt
5th row	looker

Value	Count	Frequency (%)
intel	3	0.3%
dogfood	3	0.3%
bartman	2	0.2%
rupert	2	0.2%
gonzalez	2	0.2%
daddy	2	0.2%
china	2	0.2%
gator	2	0.2%
strip	2	0.2%
kkkk	2	0.2%
Other values (925)	978	97.8%

Most occurring characters

Value	Count	Frequency (%)
e	596	9.6%
a	530	8.5%
o	481	7.7%
r	435	7.0%
n	398	6.4%
s	368	5.9%
i	357	5.7%
l	311	5.0%
t	310	5.0%
d	222	3.6%
Other values (28)	2228	35.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6236	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	596	9.6%
a	530	8.5%
o	481	7.7%
r	435	7.0%
n	398	6.4%
s	368	5.9%
i	357	5.7%
l	311	5.0%
t	310	5.0%
d	222	3.6%
Other values (28)	2228	35.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6236	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	596	9.6%
a	530	8.5%
o	481	7.7%
r	435	7.0%
n	398	6.4%
s	368	5.9%
i	357	5.7%
l	311	5.0%
t	310	5.0%
d	222	3.6%
Other values (28)	2228	35.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6236	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	596	9.6%
a	530	8.5%
o	481	7.7%
r	435	7.0%
n	398	6.4%
s	368	5.9%
i	357	5.7%
l	311	5.0%
t	310	5.0%
d	222	3.6%
Other values (28)	2228	35.7%

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	55.8 KiB

Length

Max length	8
Median length	8
Mean length	8
Min length	8

Characters and Unicode

Total characters	8000
Distinct characters	62
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	mOEoCnXa
2nd row	mH8fhDNg
3rd row	KypWHYqt
4th row	Jxv8K2wd
5th row	Z38f4AEI

Value	Count	Frequency (%)
moeocnxa	1	0.1%
rechtyqx	1	0.1%
leen31xt	1	0.1%
nnsoza6r	1	0.1%
kypwhyqt	1	0.1%
jxv8k2wd	1	0.1%
z38f4aei	1	0.1%
hvttpuvy	1	0.1%
1iby8u9q	1	0.1%
e2kq5exf	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
T	155	1.9%
j	154	1.9%
s	151	1.9%
g	150	1.9%
N	146	1.8%
f	146	1.8%
I	146	1.8%
H	146	1.8%
1	143	1.8%
h	142	1.8%
Other values (52)	6521	81.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
T	155	1.9%
j	154	1.9%
s	151	1.9%
g	150	1.9%
N	146	1.8%
f	146	1.8%
I	146	1.8%
H	146	1.8%
1	143	1.8%
h	142	1.8%
Other values (52)	6521	81.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
T	155	1.9%
j	154	1.9%
s	151	1.9%
g	150	1.9%
N	146	1.8%
f	146	1.8%
I	146	1.8%
H	146	1.8%
1	143	1.8%
h	142	1.8%
Other values (52)	6521	81.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	8000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
T	155	1.9%
j	154	1.9%
s	151	1.9%
g	150	1.9%
N	146	1.8%
f	146	1.8%
I	146	1.8%
H	146	1.8%
1	143	1.8%
h	142	1.8%
Other values (52)	6521	81.5%

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	79.2 KiB

Length

Max length	32
Median length	32
Mean length	32
Min length	32

Characters and Unicode

Total characters	32000
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	97bc1b256d3f0ee110cd09db9a06257b
2nd row	052dee40b72fc8b210ddfd6995ddb383
3rd row	03755b1d2a87d36fb7de8a9b89961613
4th row	b1b9c008a20eba775fafef4867807e08
5th row	a614cef23454186f74ae1486ae48ad88

Value	Count	Frequency (%)
97bc1b256d3f0ee110cd09db9a06257b	1	0.1%
0f4666c4cac89326dec51dd181aa9f07	1	0.1%
d5cdaf49ace3e7ce22dcf06ed42da7a3	1	0.1%
09ca9ec869cdaf0702d6d8c386ffd530	1	0.1%
03755b1d2a87d36fb7de8a9b89961613	1	0.1%
b1b9c008a20eba775fafef4867807e08	1	0.1%
a614cef23454186f74ae1486ae48ad88	1	0.1%
ed9c4d49c8245e4f8e733b9f3a1e367d	1	0.1%
9b3cf78f8eae7bec9a17c044f4fc3132	1	0.1%
9350e7502906c99d45418e6a51e178f1	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
d	2080	6.5%
8	2059	6.4%
6	2052	6.4%
2	2036	6.4%
4	2016	6.3%
7	2013	6.3%
e	2005	6.3%
c	1993	6.2%
b	1991	6.2%
3	1991	6.2%
Other values (6)	11764	36.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	32000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
d	2080	6.5%
8	2059	6.4%
6	2052	6.4%
2	2036	6.4%
4	2016	6.3%
7	2013	6.3%
e	2005	6.3%
c	1993	6.2%
b	1991	6.2%
3	1991	6.2%
Other values (6)	11764	36.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	32000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
d	2080	6.5%
8	2059	6.4%
6	2052	6.4%
2	2036	6.4%
4	2016	6.3%
7	2013	6.3%
e	2005	6.3%
c	1993	6.2%
b	1991	6.2%
3	1991	6.2%
Other values (6)	11764	36.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	32000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
d	2080	6.5%
8	2059	6.4%
6	2052	6.4%
2	2036	6.4%
4	2016	6.3%
7	2013	6.3%
e	2005	6.3%
c	1993	6.2%
b	1991	6.2%
3	1991	6.2%
Other values (6)	11764	36.8%

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	87.0 KiB

Length

Max length	40
Median length	40
Mean length	40
Min length	40

Characters and Unicode

Total characters	40000
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	4ec35e12021b3fb1deaa99b09b0f49e47cc260cd
2nd row	00f8d1c32f6717b3dbd75f1876446e0ef5fcb89b
3rd row	2efb02de4e6a388dcfcf1b2a1abfd70884e9396c
4th row	8356e5bf2cfee44f28408bfd872bd7c6f404ca8f
5th row	c750d534cf4011b3fbe8b24c92c92d6281b8e368

Value	Count	Frequency (%)
4ec35e12021b3fb1deaa99b09b0f49e47cc260cd	1	0.1%
66150842a067912142f51c0d4962b2b590afbb46	1	0.1%
feb65ef81ec95c0d7f5d4f65d858211413e1ceef	1	0.1%
6f1e3a43e80b276a2bf0e061de51c3e96b59bee5	1	0.1%
2efb02de4e6a388dcfcf1b2a1abfd70884e9396c	1	0.1%
8356e5bf2cfee44f28408bfd872bd7c6f404ca8f	1	0.1%
c750d534cf4011b3fbe8b24c92c92d6281b8e368	1	0.1%
d715a225f3d02a3eba48844e643944442a5e1d15	1	0.1%
51eb76c8173da91e6842da98e71b6985edfc3eb3	1	0.1%
1e2b7a25d9ba8648c3e5b235ae7ab5ed244b64ae	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
6	2613	6.5%
3	2584	6.5%
1	2541	6.4%
4	2528	6.3%
5	2514	6.3%
e	2510	6.3%
7	2509	6.3%
a	2483	6.2%
2	2482	6.2%
0	2478	6.2%
Other values (6)	14758	36.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	40000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
6	2613	6.5%
3	2584	6.5%
1	2541	6.4%
4	2528	6.3%
5	2514	6.3%
e	2510	6.3%
7	2509	6.3%
a	2483	6.2%
2	2482	6.2%
0	2478	6.2%
Other values (6)	14758	36.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	40000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
6	2613	6.5%
3	2584	6.5%
1	2541	6.4%
4	2528	6.3%
5	2514	6.3%
e	2510	6.3%
7	2509	6.3%
a	2483	6.2%
2	2482	6.2%
0	2478	6.2%
Other values (6)	14758	36.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	40000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
6	2613	6.5%
3	2584	6.5%
1	2541	6.4%
4	2528	6.3%
5	2514	6.3%
e	2510	6.3%
7	2509	6.3%
a	2483	6.2%
2	2482	6.2%
0	2478	6.2%
Other values (6)	14758	36.9%

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	110.5 KiB

Length

Max length	64
Median length	64
Mean length	64
Min length	64

Characters and Unicode

Total characters	64000
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1000 ?
Unique (%)	100.0%

Sample

1st row	b14e27094032c9f96907732e002fc6de1c83484cb4e41d5bd5891abe37cffc57
2nd row	a88567b713d38be8fea4a774a86b0ac81a0e6283023a30b9ab77b26125471b31
3rd row	61acb0c7e9185989ececef03aff5226d9342c5e28b80309110fc4793d5b47973
4th row	54ddc39f7d02e73935c309a28382653c64e35c68f5fd25a1275d2b22f8fd1691
5th row	5024404413d2c0829cb4e59d722278fb45e4bdd9decb1c13696145253ff7e93e

Value	Count	Frequency (%)
b14e27094032c9f96907732e002fc6de1c83484cb4e41d5bd5891abe37cffc57	1	0.1%
dd16be2a6f3d7e676f59403cb4308e24945096c80be1087806def2c391e86e4b	1	0.1%
ed6b1214dee92ed841f20f14c567fde268e4c6997bb84256d5dae39f18fd16e1	1	0.1%
47fcb7881e45e57d034fea06df24c960a6ef37c0973e2e51c3a63008cdbedda4	1	0.1%
61acb0c7e9185989ececef03aff5226d9342c5e28b80309110fc4793d5b47973	1	0.1%
54ddc39f7d02e73935c309a28382653c64e35c68f5fd25a1275d2b22f8fd1691	1	0.1%
5024404413d2c0829cb4e59d722278fb45e4bdd9decb1c13696145253ff7e93e	1	0.1%
aca4e12f0fd26720d5fa29e8f2e9ce89cbdb8cee04480f0afef5eeade4b1b81b	1	0.1%
aa435f8c7c837bb01d4cee938525693cf908f37471dc12789486879d76652fa0	1	0.1%
9cf409b1174cd4015af5799fba026f0306564b1afd98cc9f6cc4909752626155	1	0.1%
Other values (990)	990	99.0%

Most occurring characters

Value	Count	Frequency (%)
f	4158	6.5%
d	4094	6.4%
5	4070	6.4%
0	4061	6.3%
6	4061	6.3%
1	4026	6.3%
e	4021	6.3%
b	3977	6.2%
4	3972	6.2%
a	3970	6.2%
Other values (6)	23590	36.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	64000	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
f	4158	6.5%
d	4094	6.4%
5	4070	6.4%
0	4061	6.3%
6	4061	6.3%
1	4026	6.3%
e	4021	6.3%
b	3977	6.2%
4	3972	6.2%
a	3970	6.2%
Other values (6)	23590	36.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	64000	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
f	4158	6.5%
d	4094	6.4%
5	4070	6.4%
0	4061	6.3%
6	4061	6.3%
1	4026	6.3%
e	4021	6.3%
b	3977	6.2%
4	3972	6.2%
a	3970	6.2%
Other values (6)	23590	36.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	64000	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
f	4158	6.5%
d	4094	6.4%
5	4070	6.4%
0	4061	6.3%
6	4061	6.3%
1	4026	6.3%
e	4021	6.3%
b	3977	6.2%
4	3972	6.2%
a	3970	6.2%
Other values (6)	23590	36.9%

dob.date
Date

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Minimum	1944-09-06 18:54:19.939000+00:00
Maximum	2001-05-22 14:04:25.722000+00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

dob.age
Real number (ℝ)

Distinct	58
Distinct (%)	5.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	53.33

Minimum	24
Maximum	81
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	24
5-th percentile	27
Q1	39
median	54
Q3	67
95-th percentile	78
Maximum	81
Range	57
Interquartile range (IQR)	28

Descriptive statistics

Standard deviation	16.323896
Coefficient of variation (CV)	0.30609217
Kurtosis	-1.1839922
Mean	53.33
Median Absolute Deviation (MAD)	14
Skewness	-0.10907284
Sum	53330
Variance	266.46957
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
75	29	2.9%
57	24	2.4%
67	24	2.4%
62	23	2.3%
78	23	2.3%
60	23	2.3%
69	23	2.3%
47	23	2.3%
54	22	2.2%
25	22	2.2%
Other values (48)	764	76.4%

Value	Count	Frequency (%)
24	5	0.5%
25	22	2.2%
26	16	1.6%
27	18	1.8%
28	17	1.7%
29	16	1.6%
30	14	1.4%
31	19	1.9%
32	15	1.5%
33	12	1.2%

Value	Count	Frequency (%)
81	4	0.4%
80	17	1.7%
79	16	1.6%
78	23	2.3%
77	15	1.5%
76	15	1.5%
75	29	2.9%
74	17	1.7%
73	15	1.5%
72	14	1.4%

registered.date
Date

Unique

Distinct	1000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	7.9 KiB

Minimum	2002-03-21 20:52:52.614000+00:00
Maximum	2022-05-19 18:24:26.847000+00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

registered.age
Real number (ℝ)

Distinct	21
Distinct (%)	2.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.254

Minimum	3
Maximum	23
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	7.9 KiB

Quantile statistics

Minimum	3
5-th percentile	4
Q1	8
median	13
Q3	18
95-th percentile	22
Maximum	23
Range	20
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	5.8131985
Coefficient of variation (CV)	0.43859956
Kurtosis	-1.2101259
Mean	13.254
Median Absolute Deviation (MAD)	5
Skewness	-0.00017928222
Sum	13254
Variance	33.793277
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
7	59	5.9%
4	58	5.8%
9	58	5.8%
17	58	5.8%
21	58	5.8%
16	57	5.7%
11	54	5.4%
5	51	5.1%
15	51	5.1%
13	49	4.9%
Other values (11)	447	44.7%

Value	Count	Frequency (%)
3	8	0.8%
4	58	5.8%
5	51	5.1%
6	43	4.3%
7	59	5.9%
8	44	4.4%
9	58	5.8%
10	40	4.0%
11	54	5.4%
12	49	4.9%

Value	Count	Frequency (%)
23	38	3.8%
22	49	4.9%
21	58	5.8%
20	47	4.7%
19	44	4.4%
18	45	4.5%
17	58	5.8%
16	57	5.7%
15	51	5.1%
14	40	4.0%

id.name
Categorical

High correlation

Distinct	18
Distinct (%)	1.8%
Missing	0
Missing (%)	0.0%
Memory size	50.6 KiB

	197
SVNR	60
FN	60
NINO	53
SID	52
Other values (13)	578

Length

Max length	5
Median length	4
Mean length	2.698
Min length	0

Characters and Unicode

Total characters	2698
Distinct characters	16
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	UIDAI
2nd row	SVNR
3rd row	BSN
4th row	NSS
5th row	SVNR

Common Values

Value	Count	Frequency (%)
	197	19.7%
SVNR	60	6.0%
FN	60	6.0%
NINO	53	5.3%
SID	52	5.2%
INSEE	52	5.2%
PPS	51	5.1%
DNI	47	4.7%
UIDAI	46	4.6%
BSN	46	4.6%
Other values (8)	336	33.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
svnr	60	7.5%
fn	60	7.5%
nino	53	6.6%
sid	52	6.5%
insee	52	6.5%
pps	51	6.4%
dni	47	5.9%
bsn	46	5.7%
uidai	46	5.7%
cpf	45	5.6%
Other values (7)	291	36.2%

Most occurring characters

Value	Count	Frequency (%)
N	537	19.9%
S	519	19.2%
I	334	12.4%
P	188	7.0%
F	145	5.4%
D	145	5.4%
E	144	5.3%
V	104	3.9%
R	101	3.7%
A	90	3.3%
Other values (6)	391	14.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2698	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
N	537	19.9%
S	519	19.2%
I	334	12.4%
P	188	7.0%
F	145	5.4%
D	145	5.4%
E	144	5.3%
V	104	3.9%
R	101	3.7%
A	90	3.3%
Other values (6)	391	14.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2698	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
N	537	19.9%
S	519	19.2%
I	334	12.4%
P	188	7.0%
F	145	5.4%
D	145	5.4%
E	144	5.3%
V	104	3.9%
R	101	3.7%
A	90	3.3%
Other values (6)	391	14.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2698	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
N	537	19.9%
S	519	19.2%
I	334	12.4%
P	188	7.0%
F	145	5.4%
D	145	5.4%
E	144	5.3%
V	104	3.9%
R	101	3.7%
A	90	3.3%
Other values (6)	391	14.5%

id.value
Text

Missing

Distinct	803
Distinct (%)	100.0%
Missing	197
Missing (%)	19.7%
Memory size	54.1 KiB

Length

Max length	17
Median length	14
Mean length	12.033624
Min length	8

Characters and Unicode

Total characters	9663
Distinct characters	46
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	803 ?
Unique (%)	100.0%

Sample

1st row	752188464058
2nd row	58 110866 G 961
3rd row	15024616
4th row	80 42 81 1504 7
5th row	21 240597 U 175

Value	Count	Frequency (%)
89	10	0.7%
13	10	0.7%
g	9	0.6%
s	9	0.6%
10	9	0.6%
66	8	0.6%
18	8	0.6%
b	8	0.6%
09	7	0.5%
h	7	0.5%
Other values (985)	1338	94.0%

Most occurring characters

Value	Count	Frequency (%)
0	902	9.3%
1	848	8.8%
6	793	8.2%
5	784	8.1%
7	779	8.1%
2	760	7.9%
8	759	7.9%
4	709	7.3%
9	705	7.3%
3	684	7.1%
Other values (36)	1940	20.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	9663	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	902	9.3%
1	848	8.8%
6	793	8.2%
5	784	8.1%
7	779	8.1%
2	760	7.9%
8	759	7.9%
4	709	7.3%
9	705	7.3%
3	684	7.1%
Other values (36)	1940	20.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	9663	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	902	9.3%
1	848	8.8%
6	793	8.2%
5	784	8.1%
7	779	8.1%
2	760	7.9%
8	759	7.9%
4	709	7.3%
9	705	7.3%
3	684	7.1%
Other values (36)	1940	20.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	9663	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	902	9.3%
1	848	8.8%
6	793	8.2%
5	784	8.1%
7	779	8.1%
2	760	7.9%
8	759	7.9%
4	709	7.3%
9	705	7.3%
3	684	7.1%
Other values (36)	1940	20.1%

picture.large
URL

Distinct	195
Distinct (%)	19.5%
Missing	0
Missing (%)	0.0%
Memory size	93.7 KiB

https://randomuser.me/api/portraits/women/57.jpg	13
https://randomuser.me/api/portraits/men/82.jpg	13
https://randomuser.me/api/portraits/women/50.jpg	12
https://randomuser.me/api/portraits/men/59.jpg	12
https://randomuser.me/api/portraits/men/91.jpg	12
Other values (190)	938

Value	Count	Frequency (%)
https://randomuser.me/api/portraits/women/57.jpg	13	1.3%
https://randomuser.me/api/portraits/men/82.jpg	13	1.3%
https://randomuser.me/api/portraits/women/50.jpg	12	1.2%
https://randomuser.me/api/portraits/men/59.jpg	12	1.2%
https://randomuser.me/api/portraits/men/91.jpg	12	1.2%
https://randomuser.me/api/portraits/men/65.jpg	11	1.1%
https://randomuser.me/api/portraits/men/83.jpg	10	1.0%
https://randomuser.me/api/portraits/men/89.jpg	10	1.0%
https://randomuser.me/api/portraits/men/19.jpg	9	0.9%
https://randomuser.me/api/portraits/women/48.jpg	9	0.9%
Other values (185)	889	88.9%

Value	Count	Frequency (%)
https	1000	100.0%

Value	Count	Frequency (%)
randomuser.me	1000	100.0%

Value	Count	Frequency (%)
/api/portraits/women/57.jpg	13	1.3%
/api/portraits/men/82.jpg	13	1.3%
/api/portraits/women/50.jpg	12	1.2%
/api/portraits/men/59.jpg	12	1.2%
/api/portraits/men/91.jpg	12	1.2%
/api/portraits/men/65.jpg	11	1.1%
/api/portraits/men/83.jpg	10	1.0%
/api/portraits/men/89.jpg	10	1.0%
/api/portraits/men/19.jpg	9	0.9%
/api/portraits/women/48.jpg	9	0.9%
Other values (185)	889	88.9%

Value	Count	Frequency (%)
	1000	100.0%

Value	Count	Frequency (%)
	1000	100.0%

picture.medium
URL

Distinct	195
Distinct (%)	19.5%
Missing	0
Missing (%)	0.0%
Memory size	97.6 KiB

https://randomuser.me/api/portraits/med/women/57.jpg	13
https://randomuser.me/api/portraits/med/men/82.jpg	13
https://randomuser.me/api/portraits/med/women/50.jpg	12
https://randomuser.me/api/portraits/med/men/59.jpg	12
https://randomuser.me/api/portraits/med/men/91.jpg	12
Other values (190)	938

Value	Count	Frequency (%)
https://randomuser.me/api/portraits/med/women/57.jpg	13	1.3%
https://randomuser.me/api/portraits/med/men/82.jpg	13	1.3%
https://randomuser.me/api/portraits/med/women/50.jpg	12	1.2%
https://randomuser.me/api/portraits/med/men/59.jpg	12	1.2%
https://randomuser.me/api/portraits/med/men/91.jpg	12	1.2%
https://randomuser.me/api/portraits/med/men/65.jpg	11	1.1%
https://randomuser.me/api/portraits/med/men/83.jpg	10	1.0%
https://randomuser.me/api/portraits/med/men/89.jpg	10	1.0%
https://randomuser.me/api/portraits/med/men/19.jpg	9	0.9%
https://randomuser.me/api/portraits/med/women/48.jpg	9	0.9%
Other values (185)	889	88.9%

Value	Count	Frequency (%)
https	1000	100.0%

Value	Count	Frequency (%)
randomuser.me	1000	100.0%

Value	Count	Frequency (%)
/api/portraits/med/women/57.jpg	13	1.3%
/api/portraits/med/men/82.jpg	13	1.3%
/api/portraits/med/women/50.jpg	12	1.2%
/api/portraits/med/men/59.jpg	12	1.2%
/api/portraits/med/men/91.jpg	12	1.2%
/api/portraits/med/men/65.jpg	11	1.1%
/api/portraits/med/men/83.jpg	10	1.0%
/api/portraits/med/men/89.jpg	10	1.0%
/api/portraits/med/men/19.jpg	9	0.9%
/api/portraits/med/women/48.jpg	9	0.9%
Other values (185)	889	88.9%

Value	Count	Frequency (%)
	1000	100.0%

Value	Count	Frequency (%)
	1000	100.0%

picture.thumbnail
URL

Distinct	195
Distinct (%)	19.5%
Missing	0
Missing (%)	0.0%
Memory size	99.6 KiB

https://randomuser.me/api/portraits/thumb/women/57.jpg	13
https://randomuser.me/api/portraits/thumb/men/82.jpg	13
https://randomuser.me/api/portraits/thumb/women/50.jpg	12
https://randomuser.me/api/portraits/thumb/men/59.jpg	12
https://randomuser.me/api/portraits/thumb/men/91.jpg	12
Other values (190)	938

Value	Count	Frequency (%)
https://randomuser.me/api/portraits/thumb/women/57.jpg	13	1.3%
https://randomuser.me/api/portraits/thumb/men/82.jpg	13	1.3%
https://randomuser.me/api/portraits/thumb/women/50.jpg	12	1.2%
https://randomuser.me/api/portraits/thumb/men/59.jpg	12	1.2%
https://randomuser.me/api/portraits/thumb/men/91.jpg	12	1.2%
https://randomuser.me/api/portraits/thumb/men/65.jpg	11	1.1%
https://randomuser.me/api/portraits/thumb/men/83.jpg	10	1.0%
https://randomuser.me/api/portraits/thumb/men/89.jpg	10	1.0%
https://randomuser.me/api/portraits/thumb/men/19.jpg	9	0.9%
https://randomuser.me/api/portraits/thumb/women/48.jpg	9	0.9%
Other values (185)	889	88.9%

Value	Count	Frequency (%)
https	1000	100.0%

Value	Count	Frequency (%)
randomuser.me	1000	100.0%

Value	Count	Frequency (%)
/api/portraits/thumb/women/57.jpg	13	1.3%
/api/portraits/thumb/men/82.jpg	13	1.3%
/api/portraits/thumb/women/50.jpg	12	1.2%
/api/portraits/thumb/men/59.jpg	12	1.2%
/api/portraits/thumb/men/91.jpg	12	1.2%
/api/portraits/thumb/men/65.jpg	11	1.1%
/api/portraits/thumb/men/83.jpg	10	1.0%
/api/portraits/thumb/men/89.jpg	10	1.0%
/api/portraits/thumb/men/19.jpg	9	0.9%
/api/portraits/thumb/women/48.jpg	9	0.9%
Other values (185)	889	88.9%

Value	Count	Frequency (%)
	1000	100.0%

Value	Count	Frequency (%)
	1000	100.0%

Interactions

Correlations

	dob.age	gender	id.name	location.coordinates.latitude	location.coordinates.longitude	location.country	location.street.number	location.timezone.description	location.timezone.offset	name.title	nat	registered.age
dob.age	1.000	0.000	0.048	0.016	0.002	0.037	-0.028	0.000	0.000	0.000	0.037	-0.022
gender	0.000	1.000	0.121	0.000	1.000	0.154	0.064	0.098	0.098	0.997	0.154	0.026
id.name	0.048	0.121	1.000	0.000	1.000	0.998	0.035	0.000	0.000	0.397	0.998	0.000
location.coordinates.latitude	0.016	0.000	0.000	1.000	-0.040	0.025	0.045	0.045	0.045	0.038	0.025	-0.020
location.coordinates.longitude	0.002	1.000	1.000	-0.040	1.000	1.000	-0.063	1.000	1.000	1.000	1.000	0.000
location.country	0.037	0.154	0.998	0.025	1.000	1.000	0.016	0.000	0.000	0.399	1.000	0.000
location.street.number	-0.028	0.064	0.035	0.045	-0.063	0.016	1.000	0.034	0.034	0.000	0.016	0.002
location.timezone.description	0.000	0.098	0.000	0.045	1.000	0.000	0.034	1.000	1.000	0.068	0.000	0.000
location.timezone.offset	0.000	0.098	0.000	0.045	1.000	0.000	0.034	1.000	1.000	0.068	0.000	0.000
name.title	0.000	0.997	0.397	0.038	1.000	0.399	0.000	0.068	0.068	1.000	0.399	0.000
nat	0.037	0.154	0.998	0.025	1.000	1.000	0.016	0.000	0.000	0.399	1.000	0.000
registered.age	-0.022	0.026	0.000	-0.020	0.000	0.000	0.002	0.000	0.000	0.000	0.000	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

	gender	email	phone	cell	nat	name.title	name.first	name.last	location.street.number	location.street.name	location.city	location.state	location.country	location.postcode	location.coordinates.latitude	location.coordinates.longitude	location.timezone.offset	location.timezone.description	login.uuid	login.username	login.password	login.salt	login.md5	login.sha1	login.sha256	dob.date	dob.age	registered.date	registered.age	id.name	id.value	picture.large	picture.medium	picture.thumbnail
0	female	supriya.bangera@example.com	7441853155	8275260265	IN	Ms	Supriya	Bangera	5346	Hazratganj	Karimnagar	Himachal Pradesh	India	49188	11.9114	112.3948	-5:00	Eastern Time (US & Canada), Bogota, Lima	e1c48576-63a7-4373-8016-d0cf95662e96	happyswan109	asian	mOEoCnXa	97bc1b256d3f0ee110cd09db9a06257b	4ec35e12021b3fb1deaa99b09b0f49e47cc260cd	b14e27094032c9f96907732e002fc6de1c83484cb4e41d5bd5891abe37cffc57	1988-02-04T14:41:31.937Z	37	2021-02-27T05:13:43.091Z	4	UIDAI	752188464058	https://randomuser.me/api/portraits/women/57.jpg	https://randomuser.me/api/portraits/med/women/57.jpg	https://randomuser.me/api/portraits/thumb/women/57.jpg
1	female	angelika.greve@example.com	0299-7266921	0176-8590933	DE	Mrs	Angelika	Greve	7710	Parkstraße	Kuppenheim	Berlin	Germany	66234	-56.8500	9.6405	-6:00	Central Time (US & Canada), Mexico City	864c9490-4a8b-4943-8d7a-719d3b0493cb	lazymeercat294	freee	mH8fhDNg	052dee40b72fc8b210ddfd6995ddb383	00f8d1c32f6717b3dbd75f1876446e0ef5fcb89b	a88567b713d38be8fea4a774a86b0ac81a0e6283023a30b9ab77b26125471b31	1966-08-11T23:41:58.568Z	59	2012-03-10T10:27:05.516Z	13	SVNR	58 110866 G 961	https://randomuser.me/api/portraits/women/77.jpg	https://randomuser.me/api/portraits/med/women/77.jpg	https://randomuser.me/api/portraits/thumb/women/77.jpg
2	male	naim.molendijk@example.com	(073) 4576715	(06) 25012167	NL	Mr	Naïm	Molendijk	4254	Burgemeester Dohmenplein	Mook	Groningen	Netherlands	4442 MO	-7.4710	-130.8219	+9:00	Tokyo, Seoul, Osaka, Sapporo, Yakutsk	938f117a-1589-4367-83ef-b399f42bd8f0	bluewolf781	maryland	KypWHYqt	03755b1d2a87d36fb7de8a9b89961613	2efb02de4e6a388dcfcf1b2a1abfd70884e9396c	61acb0c7e9185989ececef03aff5226d9342c5e28b80309110fc4793d5b47973	1966-01-24T05:13:35.891Z	60	2007-07-03T13:13:12.738Z	18	BSN	15024616	https://randomuser.me/api/portraits/men/64.jpg	https://randomuser.me/api/portraits/med/men/64.jpg	https://randomuser.me/api/portraits/thumb/men/64.jpg
3	male	cristobal.trevino@example.com	(614) 832 1069	(672) 391 7823	MX	Mr	Cristobal	Treviño	6391	Privada Sur Madrigal	General Zaragoza	Queretaro	Mexico	84423	80.7841	-63.6445	-4:00	Atlantic Time (Canada), Caracas, La Paz	69e2b7a7-d638-4539-a4c8-c4492ec64ab5	blackostrich700	hunt	Jxv8K2wd	b1b9c008a20eba775fafef4867807e08	8356e5bf2cfee44f28408bfd872bd7c6f404ca8f	54ddc39f7d02e73935c309a28382653c64e35c68f5fd25a1275d2b22f8fd1691	1994-04-16T19:30:58.069Z	31	2019-06-13T14:48:51.163Z	6	NSS	80 42 81 1504 7	https://randomuser.me/api/portraits/men/29.jpg	https://randomuser.me/api/portraits/med/men/29.jpg	https://randomuser.me/api/portraits/thumb/men/29.jpg
4	male	francesco.ulrich@example.com	0231-2739158	0178-6362153	DE	Mr	Francesco	Ulrich	4866	Goethestraße	Gräfenhainichen	Hessen	Germany	76615	-16.1104	32.1274	+5:30	Bombay, Calcutta, Madras, New Delhi	bab2865c-7349-48f6-b812-429b28037a1a	blackcat544	looker	Z38f4AEI	a614cef23454186f74ae1486ae48ad88	c750d534cf4011b3fbe8b24c92c92d6281b8e368	5024404413d2c0829cb4e59d722278fb45e4bdd9decb1c13696145253ff7e93e	1997-05-24T06:14:43.269Z	28	2006-09-15T00:01:05.686Z	19	SVNR	21 240597 U 175	https://randomuser.me/api/portraits/men/69.jpg	https://randomuser.me/api/portraits/med/men/69.jpg	https://randomuser.me/api/portraits/thumb/men/69.jpg
5	female	hetal.anchan@example.com	9483239909	7698440169	IN	Miss	Hetal	Anchan	3404	Tripolia Bazar	Phusro	Jammu and Kashmir	India	22164	-16.8659	-33.4417	+7:00	Bangkok, Hanoi, Jakarta	6478a13e-4ad5-4ad9-a5f9-d5072aadd417	purpleleopard193	shark1	hVtTpUvY	ed9c4d49c8245e4f8e733b9f3a1e367d	d715a225f3d02a3eba48844e643944442a5e1d15	aca4e12f0fd26720d5fa29e8f2e9ce89cbdb8cee04480f0afef5eeade4b1b81b	1983-05-06T22:23:50.780Z	42	2005-03-23T09:09:12.984Z	20	UIDAI	881290974618	https://randomuser.me/api/portraits/women/79.jpg	https://randomuser.me/api/portraits/med/women/79.jpg	https://randomuser.me/api/portraits/thumb/women/79.jpg
6	female	sedef.eksioglu@example.com	(637)-503-5801	(466)-824-5003	TR	Ms	Sedef	Ekşioğlu	4934	Bağdat Cd	Mersin	Çorum	Turkey	17190	57.8666	-71.2382	+1:00	Brussels, Copenhagen, Madrid, Paris	421afc35-e2bd-444d-863d-21816b374eb7	redzebra223	honey1	1IbY8U9q	9b3cf78f8eae7bec9a17c044f4fc3132	51eb76c8173da91e6842da98e71b6985edfc3eb3	aa435f8c7c837bb01d4cee938525693cf908f37471dc12789486879d76652fa0	1969-03-30T00:40:34.618Z	56	2018-05-29T09:17:19.111Z	7		None	https://randomuser.me/api/portraits/women/63.jpg	https://randomuser.me/api/portraits/med/women/63.jpg	https://randomuser.me/api/portraits/thumb/women/63.jpg
7	female	ozsu.karaer@example.com	(903)-072-1867	(483)-380-3061	TR	Miss	Özsu	Karaer	9412	Atatürk Sk	Hatay	Tekirdağ	Turkey	63586	-23.2668	-62.6245	+10:00	Eastern Australia, Guam, Vladivostok	6bdef1e6-7882-427e-bb46-24b6e18dda4a	orangecat258	method	E2KQ5eXF	9350e7502906c99d45418e6a51e178f1	1e2b7a25d9ba8648c3e5b235ae7ab5ed244b64ae	9cf409b1174cd4015af5799fba026f0306564b1afd98cc9f6cc4909752626155	1959-05-19T04:42:32.019Z	66	2009-07-20T07:18:58.912Z	16		None	https://randomuser.me/api/portraits/women/64.jpg	https://randomuser.me/api/portraits/med/women/64.jpg	https://randomuser.me/api/portraits/thumb/women/64.jpg
8	male	matteo.andre@example.com	078 409 78 21	075 528 12 09	CH	Monsieur	Matteo	Andre	1753	Rue de la Barre	Weiach	Neuchâtel	Switzerland	1955	-46.8630	-115.6958	-9:00	Alaska	943598c4-00d5-4fb6-a2c4-b3b5dca81a2d	silverrabbit936	swordfish	FSymfH0w	8be930b9e7a17d15a897375ec8852f0c	13b45871606e2a7e2f5da94869b57670e77d0559	a73ae1c70c31f4861b47443f3ab6b19896f013e98c328f7a686c7a2b3d1b94ae	1955-08-12T23:29:44.700Z	70	2004-02-21T10:50:33.563Z	21	AVS	756.3785.9161.29	https://randomuser.me/api/portraits/men/13.jpg	https://randomuser.me/api/portraits/med/men/13.jpg	https://randomuser.me/api/portraits/thumb/men/13.jpg
9	female	josefine.johansen@example.com	52496634	14576840	DK	Mrs	Josefine	Johansen	3749	Rønne Alle	Jystrup	Danmark	Denmark	79061	46.4164	-3.9195	-6:00	Central Time (US & Canada), Mexico City	d546fe0f-1aed-4771-aafd-e23f0fc6a1ed	redostrich373	asd123	jNfLSErU	0313b2ac4e630a0852f0dc3eb2f3dc73	5959e0d3edd7d6dc2d6f93029ab1f1325ff56571	259f0edffe471229eecb7dc9e0ee9d9c6c2c03b86fdadc87ede1e7b3eb262c11	1979-01-21T15:39:57.279Z	47	2022-05-17T15:56:01.103Z	3	CPR	210179-2939	https://randomuser.me/api/portraits/women/85.jpg	https://randomuser.me/api/portraits/med/women/85.jpg	https://randomuser.me/api/portraits/thumb/women/85.jpg

	gender	email	phone	cell	nat	name.title	name.first	name.last	location.street.number	location.street.name	location.city	location.state	location.country	location.postcode	location.coordinates.latitude	location.coordinates.longitude	location.timezone.offset	location.timezone.description	login.uuid	login.username	login.password	login.salt	login.md5	login.sha1	login.sha256	dob.date	dob.age	registered.date	registered.age	id.name	id.value	picture.large	picture.medium	picture.thumbnail
990	female	hiya.nair@example.com	8214983268	8391095374	IN	Miss	Hiya	Nair	9650	College St	Panihati	Goa	India	98889	-44.2575	2.3366	-3:30	Newfoundland	71a8398a-6f31-4f48-a40b-b4e4b207466f	smallsnake258	raven	OKT0XySG	8c4aca3a3a22098bfa54da6a02791e2b	617d661bdb07894af22127b8a6b41663ab408b23	6cbce57d984fa115b813e14034f1135b013da3be748a6f8e1365d9fdf31f521d	1994-09-01T22:39:33.219Z	31	2002-12-28T11:37:29.372Z	23	UIDAI	335701167606	https://randomuser.me/api/portraits/women/73.jpg	https://randomuser.me/api/portraits/med/women/73.jpg	https://randomuser.me/api/portraits/thumb/women/73.jpg
991	male	matteo.grosse@example.com	0506-4287933	0173-5380073	DE	Mr	Matteo	Große	6763	Ahornweg	Prignitz	Hessen	Germany	21314	-59.7420	-57.5087	+4:00	Abu Dhabi, Muscat, Baku, Tbilisi	85732640-c2df-4888-93a4-4bd55b0e9c90	whitegorilla321	cyclops	6qcPLm8v	1c7721ee65d571869dc45216e688abe6	41855c3710402e55c03215d10a51f1c5734eb84f	d547f78e9ec8d601cfff3c1cef6e403c6e027fc96a09cbb470e5bcf03c07e6e9	1966-09-22T22:41:41.577Z	59	2005-11-13T14:38:46.276Z	20	SVNR	64 220966 G 095	https://randomuser.me/api/portraits/men/27.jpg	https://randomuser.me/api/portraits/med/men/27.jpg	https://randomuser.me/api/portraits/thumb/men/27.jpg
992	female	marie.andersen@example.com	44635905	53168352	DK	Ms	Marie	Andersen	4372	Vesterhavsvej	Beder	Hovedstaden	Denmark	75627	-6.1456	-94.1104	+6:00	Almaty, Dhaka, Colombo	173048ef-fd30-47e8-8ddc-7c88153c98e2	sadpeacock294	gagged	BpashVG1	e046ade80035a4ce68bd7ec594598e4b	460d3e104b08af4fdffd789b70bc36c7e6356c70	42065cf6aea894b0b1a60c0437697ee4a057ca77775d54c04a3a4f20457b0676	1988-08-18T18:19:52.507Z	37	2014-12-01T23:18:43.427Z	11	CPR	180888-5612	https://randomuser.me/api/portraits/women/76.jpg	https://randomuser.me/api/portraits/med/women/76.jpg	https://randomuser.me/api/portraits/thumb/women/76.jpg
993	female	suzanne.ward@example.com	(793) 625-2132	(469) 639-7457	US	Mrs	Suzanne	Ward	9059	Green Rd	Red Bluff	New York	United States	12092	-67.7184	3.0612	+2:00	Kaliningrad, South Africa	77a3598a-1913-49a1-a9a3-7263c8886c3d	yellowpeacock670	swimmer	pDImRo4v	d6f166e35c006310e0ff4467722899da	c1382c9e105aa48a425cb7069a48e4cc8f9a95df	dc2c46d8394c327dc6797d0dbc511cd5a66893ac6cf62eb3737f9aaedd4d8ce2	1988-02-24T12:33:32.506Z	37	2022-01-07T05:48:23.826Z	4	SSN	465-49-5809	https://randomuser.me/api/portraits/women/61.jpg	https://randomuser.me/api/portraits/med/women/61.jpg	https://randomuser.me/api/portraits/thumb/women/61.jpg
994	male	william.christiansen@example.com	61232110	45032697	DK	Mr	William	Christiansen	9466	Valdemarsgade	Argerskov	Midtjylland	Denmark	82867	81.1378	168.3195	-6:00	Central Time (US & Canada), Mexico City	e9bf3a1c-0163-4ba6-92b8-9287a9ac17f4	blacktiger851	rockwell	ugx4RpWm	922e8e957c6e48e01a2d543ae9e79fe1	b33d553deac53bbc088ffd8f842cc95e5fb1e36f	42f879fad2332dcb2859b7177c075fb97619cd535a1e7d8b141f2e61df7b36dc	1998-02-08T10:54:31.203Z	27	2008-06-03T03:40:17.088Z	17	CPR	080298-2068	https://randomuser.me/api/portraits/men/4.jpg	https://randomuser.me/api/portraits/med/men/4.jpg	https://randomuser.me/api/portraits/thumb/men/4.jpg
995	female	macy.liefhebber@example.com	(063) 6105756	(06) 47986730	NL	Miss	Macy	Liefhebber	1961	Erasmushof	Drechterland	Groningen	Netherlands	1333 EU	8.5337	-46.6678	+10:00	Eastern Australia, Guam, Vladivostok	015b71cf-3d32-43ab-bfca-26d6ce6d4159	tinyzebra498	verona	hDHIVLrF	af9211b095c44526af635d21189571f7	37bc6aab88a3c33f8524ee539b2c22bc8cdd24ec	9d12ec7c9645f9c76badb486b3c90e5a83e49de0fcf6c142beb85c533d438b1a	1973-04-11T14:43:06.950Z	52	2019-03-12T17:09:36.848Z	6	BSN	44744391	https://randomuser.me/api/portraits/women/81.jpg	https://randomuser.me/api/portraits/med/women/81.jpg	https://randomuser.me/api/portraits/thumb/women/81.jpg
996	female	tilde.petersen@example.com	36833841	88821525	DK	Mrs	Tilde	Petersen	6515	Vesterbyvej	Kvistgaard	Hovedstaden	Denmark	55055	13.6307	75.7416	+4:00	Abu Dhabi, Muscat, Baku, Tbilisi	2ec6ac5b-fae2-4c80-a38a-8a8e92ec30fd	purplesnake570	yomama	RY8I9uAa	1a08634fde98246fe3ab28ab754e4d56	9d700773566eb33b65b7b9031d7fe54a39667629	14935aaa0b0e6308e33588572d2d0d29052712937b1178f83110c4bf7063fc4e	1971-12-21T08:04:34.850Z	54	2017-10-29T07:38:25.425Z	8	CPR	211271-6245	https://randomuser.me/api/portraits/women/29.jpg	https://randomuser.me/api/portraits/med/women/29.jpg	https://randomuser.me/api/portraits/thumb/women/29.jpg
997	male	matteo.renard@example.com	02-29-46-19-21	06-36-47-78-05	FR	Mr	Matteo	Renard	2992	Rue de Cuire	Bordeaux	Seine-Saint-Denis	France	80727	32.8859	165.0030	+3:30	Tehran	54ebe75d-c8bb-4caa-9d5d-93ae465ba39b	orangepanda471	miao	R0JanBgK	40d5fe2ea6893b631294d586eb168bce	a3fcc11a7ad3933c69a427c25ac38aac9e4112d5	cd7d6f984c3ac7408f6048c7265b8bef57f00767eb32842fb17567c958add941	1981-07-25T09:41:25.035Z	44	2018-08-08T15:40:37.166Z	7	INSEE	1810697782961 77	https://randomuser.me/api/portraits/men/42.jpg	https://randomuser.me/api/portraits/med/men/42.jpg	https://randomuser.me/api/portraits/thumb/men/42.jpg
998	male	jochem.teunissen@example.com	(026) 7699047	(06) 47784834	NL	Mr	Jochem	Teunissen	4144	Generaal Eisenhowerplein	Saaxumhuizen	Utrecht	Netherlands	3195 MI	51.3015	-166.7184	-8:00	Pacific Time (US & Canada)	a519e5f2-10ac-4d93-81a8-a92913b455cd	redlion249	otis	jb3Ce82q	188220fdaaf17584aad84f41acbcbfd4	861303e9942ef99eb19c83e55d47a68952bf6b90	3cdee6a2a7c15d7bc3c6d890fe09e946b3ee9dab03dd001c8906e6a4b68b1b88	1965-07-27T15:27:30.153Z	60	2012-10-02T12:52:49.084Z	13	BSN	41762767	https://randomuser.me/api/portraits/men/14.jpg	https://randomuser.me/api/portraits/med/men/14.jpg	https://randomuser.me/api/portraits/thumb/men/14.jpg
999	male	franz-josef.geppert@example.com	0346-2584577	0178-6363619	DE	Mr	Franz-Josef	Geppert	5333	Blumenstraße	Reutlingen	Sachsen	Germany	36260	-66.3979	24.2801	-9:00	Alaska	45503b44-c44b-4097-9f15-05797f930967	bluebear556	rt6ytere	TuhpEkw4	bdd46faac40702f769cf7ee602754c86	6e9108bc5b686602d56d844301c8eb696edbc5b5	0ae96c0c461244b0996515b3cb631529d89ce54f9857f92925e76d5c01d1487b	1965-04-11T14:48:17.929Z	60	2013-04-03T04:36:49.305Z	12	SVNR	70 110465 G 314	https://randomuser.me/api/portraits/men/83.jpg	https://randomuser.me/api/portraits/med/men/83.jpg	https://randomuser.me/api/portraits/thumb/men/83.jpg

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)